Recurrent neural networks (RNNs) have recently produced record setting performance in language modeling and word-labeling tasks. In the word-labeling task a RNN tagger is used analogously to the more traditional conditional random field (CRF) to assign a label to each word in an input sequence. In contrast to CRFs, RNNs operate in an online fashion to assign labels as soon as a word is seen, rather than after seeing the whole word sequence.